Principal AI Engineer
AlixPartners - New York
Posted May 8, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Principal AI Engineer New York At AlixPartners, we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve. We hold ourselves accountable by providing space for authenticity, growth, and equity for everyone. AlixPartners has embraced a hybrid work model to provide flexibility and support work-life integration. Travel is part of this position, but frequency may vary based on client, team, and individual circumstances. Relocation assistance is not available for this position. About the Role The Principal AI Engineer sits at the intersection of software engineering, data science, platform architecture, and AI governance. You will be the technical owner of how AI/ML engineering is designed, built, governed, and shipped across a portfolio of products serving all of AlixPartners' domains. This is a hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, building internal developer tooling, leading security and governance design, and mentoring engineering teams. Your success is measured by team-level outcomes - scalable patterns that outlast your direct involvement. What You'll Do AI Productization & Platform Engineering - Design and own the firm's AI productization & governance playbook, covering service patterns, security/compliance standards, model evaluation rubrics, and production-readiness criteria. - Build and maintain reusable internal tooling, including AI service scaffolding, evaluation and monitoring tooling, and data infrastructure - designed for team adoption without ongoing hand-holding. - Establish AI
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